A study by former Harvard fellow Mark McGovern, PhD, along with faculty members David Canning, PhD, and Till Bärnighausen, PhD, and colleagues, has found that efforts to scale up HIV testing through home-based testing are supported by offering a $5 dollar (US) food voucher to residents in South Africa.
How can you statistically correct for missing data and selection bias in HIV prevalence estimates?
Missing data is a common problem in HIV research due to non-participation in testing, and selection bias can occur if non-participation in testing is associated with HIV status. For example, longitudinal data suggests that individuals who know or suspect that they are HIV positive are less likely to participate in HIV surveys. Four researchers from Harvard Pop Center, including Mark McGovern, PhD, Till Bärnighausen, MD, Joshua Salomon, PhD, and David Canning,…
New approach for estimating HIV prevalence
Harvard Pop Center PGDA Fellow Mark McGovern, PhD, and faculty member Till Bärnighausen, MD, have co-authored a study published in Epidemiology that explores the usefulness of applying copula functions to the more standard selection model in order to more accurately evaluate HIV prevalence estimates.